Articles | Volume 25, issue 20
https://doi.org/10.5194/acp-25-13527-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-25-13527-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
23 Oct 2025
Research article |
| 23 Oct 2025
| 23 Oct 2025
Estimating surface sulfur dioxide concentrations from satellite data over eastern China: Using chemical transport models vs. machine learning
Department of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, AL 35758, USA
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
NASA Goddard Space Flight Center, Greenbelt, MD 20771, USA
Goddard Earth Sciences Technology and Research (GESTAR) II, Morgan State University, Baltimore, MD 21251, USA
Sean W. Freeman
Department of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, AL 35758, USA
Huanxin Zhang
Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, and Iowa Technology Institute, The University of Iowa, Iowa City, Iowa 52240, USA
Department of Chemical and Biochemical Engineering, Center for Global and Regional Environmental Research, and Iowa Technology Institute, The University of Iowa, Iowa City, Iowa 52240, USA
Department of Atmospheric and Earth Science, University of Alabama in Huntsville, Huntsville, AL 35758, USA
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Pravash Tiwari, Jason Blake Cohen, Hongrui Gao, Lingxiao Lu, Jun Wang, Oleg Dubovik, and Kai Qin
EGUsphere, https://doi.org/10.5194/egusphere-2026-363, https://doi.org/10.5194/egusphere-2026-363, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Uncertainties in black carbon forcing persist due to the complex interplay of its microphysical properties. In this study, we integrated observations with physics-based simulations and machine learning to link microphysical variability to regional instantaneous forcing. We reveal that black carbon can either warm or cool the top of the atmosphere depending on its microphysics and abundance. Such nonlinear interactions must be explicitly considered to improve future radiative assessments.
Jiajun Xiong, Yi Wang, Jun Wang, Yanyu Wang, Meng Zhou, Minghui Tao, Wenhui Dong, Jhoon Kim, and Lunche Wang
EGUsphere, https://doi.org/10.5194/egusphere-2026-397, https://doi.org/10.5194/egusphere-2026-397, 2026
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
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Current models struggle to simulate aerosol extinction profiles accurately. We introduce a physics-informed deep learning framework combining model simulations with satellite data to reconstruct precise three-dimensional aerosol fields. This method significantly reduces biases over East Asia and works effectively in North America without retraining. Crucially, it acts as a diagnostic tool to identify specific physical flaws in models, guiding improvements for climate research.
Robert J. D. Spurr, Matt Christi, Nickolay A. Krotkov, Won-Ei Choi, Simon Carn, Can Li, Natalya Kramarova, David Haffner, Eun-Su Yang, Nick Gorkavyi, Alexander Vasilkov, Krzysztof Wargan, Omar Torres, Diego Loyola, Serena Di Pede, J. Pepijn Veefkind, Parker Case, Thomas Schroeder, and Pawan K. Bhartia
Atmos. Meas. Tech., 19, 993–1021, https://doi.org/10.5194/amt-19-993-2026, https://doi.org/10.5194/amt-19-993-2026, 2026
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The submarine eruption of the Hunga volcano released water vapor and sulfur dioxide directly into the stratosphere. The sulfur dioxide formed sulfuric acid aerosols leading to increased scattering of solar ultraviolet radiation (UV), interfering with satellite ozone retrievals. We present a new satellite technique for deriving the amount and height of Hunga aerosols from UV measurements, revealing an unusually low sulfuric acid concentration due to the water-rich conditions in the fresh plume.
Huanxin Zhang, Jun Wang, Nathan Janechek, Cui Ge, Meng Zhou, Lorena Castro GarcÃa, Tong Sha, Yanyu Wang, Weizhi Deng, Zhixin Xue, Chengzhe Li, Lakhima Chutia, Yi Wang, Sebastian Val, James L. McDuffie, Sina Hasheminassab, Scott E. Gluck, David J. Diner, Peter R. Colarco, Arlindo M. da Silva, and Jhoon Kim
Geosci. Model Dev., 18, 9061–9099, https://doi.org/10.5194/gmd-18-9061-2025, https://doi.org/10.5194/gmd-18-9061-2025, 2025
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We present the development of the Unified Inputs (of initial and boundary conditions) for WRF (Weather Research and Forecasting)-Chem (UI-WRF-Chem) framework to support the Multi-Angle Imager for Aerosols (MAIA) satellite mission. Major updates include improving dust size distribution in the chemical boundary conditions, updating land surface properties using recent available satellite data and enhancing the representation of soil NOx emissions. We demonstrate subsequent model improvements over several of the MAIA target areas.
Corey G. Amiot, Timothy J. Lang, Susan C. van den Heever, Richard A. Ferrare, Ousmane O. Sy, Lawrence D. Carey, Sundar A. Christopher, John R. Mecikalski, Sean W. Freeman, George Alexander Sokolowsky, Chris A. Hostetler, and Simone Tanelli
Atmos. Chem. Phys., 25, 12335–12355, https://doi.org/10.5194/acp-25-12335-2025, https://doi.org/10.5194/acp-25-12335-2025, 2025
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Decoupling aerosol and environmental impacts on convection is challenging. Using airborne data, we correlated convective metrics with aerosol concentrations in several different environments. Results were mixed, but some comparisons suggest that medium-to-high aerosol concentrations were occasionally strongly correlated with convective intensity and prevalence, especially when the atmosphere was relatively unstable. It is important to consider storm environment when evaluating aerosol effects.
Xin Xi, Jun Wang, Zhendong Lu, Andrew M. Sayer, Jaehwa Lee, Robert C. Levy, Yujie Wang, Alexei Lyapustin, Hongqing Liu, Istvan Laszlo, Changwoo Ahn, Omar Torres, Sabur Abdullaev, James Limbacher, and Ralph A. Kahn
Atmos. Chem. Phys., 25, 7403–7429, https://doi.org/10.5194/acp-25-7403-2025, https://doi.org/10.5194/acp-25-7403-2025, 2025
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The Aralkum Desert is challenging for aerosol retrieval due to its bright, heterogeneous, and dynamic surfaces and the lack of in situ constraints on aerosol properties. The performance and consistency of satellite algorithms in observing Aralkum-generated saline dust remain unknown. This study compares multisensor UVAI (ultraviolet aerosol index), AOD (aerosol optical depth), and ALH (aerosol layer height) products and reveals inconsistencies and potential biases over the Aral Sea basin.
Hyerim Kim, Xi Chen, Jun Wang, Zhendong Lu, Meng Zhou, Gregory R. Carmichael, Sang Seo Park, and Jhoon Kim
Atmos. Meas. Tech., 18, 327–349, https://doi.org/10.5194/amt-18-327-2025, https://doi.org/10.5194/amt-18-327-2025, 2025
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We compare passive aerosol layer height (ALH) retrievals from the Earth Polychromatic Imaging Camera (EPIC), TROPOspheric Monitoring Instrument (TROPOMI), and Geostationary Environment Monitoring Spectrometer (GEMS) with lidar. GEMS shows a lower correlation (R = 0.64) than EPIC and TROPOMI (R > 0.7) but with minimal bias (0.1 km vs. overestimated by ~0.8 km). GEMS performance is improved for an ultraviolet aerosol index ≥ 3. EPIC and GEMS ALH diurnal variation differs slightly.
Sean W. Freeman, Jennie Bukowski, Leah D. Grant, Peter J. Marinescu, J. Minnie Park, Stacey M. Hitchcock, Christine A. Neumaier, and Susan C. van den Heever
EGUsphere, https://doi.org/10.5194/egusphere-2024-2425, https://doi.org/10.5194/egusphere-2024-2425, 2025
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In this work, we tested different placements of a temperature and humidity sensor onboard a drone to understand what the relative errors are. Understanding these errors is critical as we want to collect more meteorological data from non-specialized platforms, such as drone swarms and drone package delivery.
Bryan N. Duncan, Daniel C. Anderson, Arlene M. Fiore, Joanna Joiner, Nickolay A. Krotkov, Can Li, Dylan B. Millet, Julie M. Nicely, Luke D. Oman, Jason M. St. Clair, Joshua D. Shutter, Amir H. Souri, Sarah A. Strode, Brad Weir, Glenn M. Wolfe, Helen M. Worden, and Qindan Zhu
Atmos. Chem. Phys., 24, 13001–13023, https://doi.org/10.5194/acp-24-13001-2024, https://doi.org/10.5194/acp-24-13001-2024, 2024
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Trace gases emitted to or formed within the atmosphere may be chemically or physically removed from the atmosphere. One trace gas, the hydroxyl radical (OH), is responsible for initiating the chemical removal of many trace gases, including some greenhouse gases. Despite its importance, scientists have not been able to adequately measure OH. In this opinion piece, we discuss promising new methods to indirectly constrain OH using satellite data of trace gases that control the abundance of OH.
Lee Tiszenkel, James H. Flynn, and Shan-Hu Lee
Atmos. Chem. Phys., 24, 11351–11363, https://doi.org/10.5194/acp-24-11351-2024, https://doi.org/10.5194/acp-24-11351-2024, 2024
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Ammonia and amines are important ingredients for aerosol formation in urban environments, but the measurements of these compounds are extremely challenging. Our observations show that urban ammonia and amines in Houston are emitted from urban sources, and diurnal variations in their concentrations are likely governed by gas-to-particle conversion and emissions.
Can Li, Nickolay A. Krotkov, Joanna Joiner, Vitali Fioletov, Chris McLinden, Debora Griffin, Peter J. T. Leonard, Simon Carn, Colin Seftor, and Alexander Vasilkov
Earth Syst. Sci. Data, 16, 4291–4309, https://doi.org/10.5194/essd-16-4291-2024, https://doi.org/10.5194/essd-16-4291-2024, 2024
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Sulfur dioxide (SO2), a poisonous gas from human activities and volcanoes, causes air pollution, acid rain, and changes to climate and the ozone layer. Satellites have been used to monitor SO2 globally, including remote areas. Here we describe a new satellite SO2 dataset from the OMPS instrument that flies on the N20 satellite. Results show that the new dataset agrees well with the existing ones from other satellites and can help to continue the global monitoring of SO2 from space.
Vignesh Vasudevan-Geetha, Lee Tiszenkel, Zhizhao Wang, Robin Russo, Daniel Bryant, Julia Lee-Taylor, Kelley Barsanti, and Shan-Hu Lee
EGUsphere, https://doi.org/10.5194/egusphere-2024-2454, https://doi.org/10.5194/egusphere-2024-2454, 2024
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Our laboratory experiments using two high-resolution mass spectrometers show that these OOMs can also form within the particle phase, in addition to gas-to-particle conversion processes. Our results demonstrate that particle-phase formation processes can contribute to the formation and growth of new particles in biogenic environments.
Tong Sha, Siyu Yang, Qingcai Chen, Liangqing Li, Xiaoyan Ma, Yan-Lin Zhang, Zhaozhong Feng, K. Folkert Boersma, and Jun Wang
Atmos. Chem. Phys., 24, 8441–8455, https://doi.org/10.5194/acp-24-8441-2024, https://doi.org/10.5194/acp-24-8441-2024, 2024
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Using an updated soil reactive nitrogen emission scheme in the Unified Inputs for Weather Research and Forecasting coupled with Chemistry (UI-WRF-Chem) model, we investigate the role of soil NO and HONO (Nr) emissions in air quality and temperature in North China. Contributions of soil Nr emissions to O3 and secondary pollutants are revealed, exceeding effects of soil NOx or HONO emission. Soil Nr emissions play an important role in mitigating O3 pollution and addressing climate change.
G. Alexander Sokolowsky, Sean W. Freeman, William K. Jones, Julia Kukulies, Fabian Senf, Peter J. Marinescu, Max Heikenfeld, Kelcy N. Brunner, Eric C. Bruning, Scott M. Collis, Robert C. Jackson, Gabrielle R. Leung, Nils Pfeifer, Bhupendra A. Raut, Stephen M. Saleeby, Philip Stier, and Susan C. van den Heever
Geosci. Model Dev., 17, 5309–5330, https://doi.org/10.5194/gmd-17-5309-2024, https://doi.org/10.5194/gmd-17-5309-2024, 2024
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Building on previous analysis tools developed for atmospheric science, the original release of the Tracking and Object-Based Analysis (tobac) Python package, v1.2, was open-source, modular, and insensitive to the type of gridded input data. Here, we present the latest version of tobac, v1.5, which substantially improves scientific capabilities and computational efficiency from the previous version. These enhancements permit new uses for tobac in atmospheric science and potentially other fields.
Zhendong Lu, Jun Wang, Yi Wang, Daven K. Henze, Xi Chen, Tong Sha, and Kang Sun
Atmos. Chem. Phys., 24, 7793–7813, https://doi.org/10.5194/acp-24-7793-2024, https://doi.org/10.5194/acp-24-7793-2024, 2024
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In contrast with past work showing that the reduction of emissions was the dominant factor for the nationwide increase of surface O3 during the lockdown in China, this study finds that the variation in meteorology (temperature and other parameters) plays a more important role. This result is obtained through sensitivity simulations using a chemical transport model constrained by satellite (TROPOMI) data and calibrated with surface observations.
Fei Liu, Steffen Beirle, Joanna Joiner, Sungyeon Choi, Zhining Tao, K. Emma Knowland, Steven J. Smith, Daniel Q. Tong, Siqi Ma, Zachary T. Fasnacht, and Thomas Wagner
Atmos. Chem. Phys., 24, 3717–3728, https://doi.org/10.5194/acp-24-3717-2024, https://doi.org/10.5194/acp-24-3717-2024, 2024
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Using satellite data, we developed a coupled method independent of the chemical transport model to map NOx emissions across US cities. After validating our technique with synthetic data, we charted NOx emissions from 2018–2021 in 39 cities. Our results closely matched EPA estimates but also highlighted some inconsistencies in both magnitude and spatial distribution. This research can help refine strategies for monitoring and managing air quality.
Tianle Yuan, Fei Liu, Lok N. Lamsal, and Hua Song
EGUsphere, https://doi.org/10.22541/essoar.168771101.14987378/v1, https://doi.org/10.22541/essoar.168771101.14987378/v1, 2023
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We train and apply a state-of-the-art deep learning model to detect NO2 plumes emitted by ships using NO2 retrievals from TROPOMI. By applying the model, we can detect individual plumes with excellent fidelity. The aggregated data show major shipping routes, but miss other routes. The missing routes are due to high cloudiness. Our method can be potentially useful for monitoring ship emissions of NOx and verifying compliance of emission standards.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Nickolay A. Krotkov, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Atmos. Meas. Tech., 16, 5575–5592, https://doi.org/10.5194/amt-16-5575-2023, https://doi.org/10.5194/amt-16-5575-2023, 2023
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Snow-covered terrain, with its high reflectance in the UV, typically enhances satellite sensitivity to boundary layer pollution. However, a significant fraction of high-quality cloud-free measurements over snow is currently excluded from analyses. In this study, we investigated how satellite SO2 measurements over snow-covered surfaces can be used to improve estimations of annual SO2 emissions.
Qindan Zhu, Bryan Place, Eva Y. Pfannerstill, Sha Tong, Huanxin Zhang, Jun Wang, Clara M. Nussbaumer, Paul Wooldridge, Benjamin C. Schulze, Caleb Arata, Anthony Bucholtz, John H. Seinfeld, Allen H. Goldstein, and Ronald C. Cohen
Atmos. Chem. Phys., 23, 9669–9683, https://doi.org/10.5194/acp-23-9669-2023, https://doi.org/10.5194/acp-23-9669-2023, 2023
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Nitrogen oxide (NOx) is a hazardous air pollutant, and it is the precursor of short-lived climate forcers like tropospheric ozone and aerosol particles. While NOx emissions from transportation has been strictly regulated, soil NOx emissions are overlooked. We use the airborne flux measurements to observe NOx emissions from highways and urban and cultivated soil land cover types. We show non-negligible soil NOx emissions, which are significantly underestimated in current model simulations.
Ruijun Dang, Daniel J. Jacob, Viral Shah, Sebastian D. Eastham, Thibaud M. Fritz, Loretta J. Mickley, Tianjia Liu, Yi Wang, and Jun Wang
Atmos. Chem. Phys., 23, 6271–6284, https://doi.org/10.5194/acp-23-6271-2023, https://doi.org/10.5194/acp-23-6271-2023, 2023
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We use the GEOS-Chem model to better understand the magnitude and trend in free tropospheric NO2 over the contiguous US. Model underestimate of background NO2 is largely corrected by considering aerosol nitrate photolysis. Increase in aircraft emissions affects satellite retrievals by altering the NO2 shape factor, and this effect is expected to increase in future. We show the importance of properly accounting for the free tropospheric background in interpreting NO2 observations from space.
Joanna Joiner, Sergey Marchenko, Zachary Fasnacht, Lok Lamsal, Can Li, Alexander Vasilkov, and Nickolay Krotkov
Atmos. Meas. Tech., 16, 481–500, https://doi.org/10.5194/amt-16-481-2023, https://doi.org/10.5194/amt-16-481-2023, 2023
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Nitrogen dioxide (NO2) is an important trace gas for both air quality and climate. NO2 affects satellite ocean color products. A new ocean color instrument – OCI (Ocean Color Instrument) – will be launched in 2024 on a NASA satellite. We show that it will be possible to measure NO2 from OCI even though it was not designed for this. The techniques developed here, based on machine learning, can also be applied to instruments already in space to speed up algorithms and reduce the effects of noise.
Jing Wei, Zhanqing Li, Jun Wang, Can Li, Pawan Gupta, and Maureen Cribb
Atmos. Chem. Phys., 23, 1511–1532, https://doi.org/10.5194/acp-23-1511-2023, https://doi.org/10.5194/acp-23-1511-2023, 2023
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This study estimated the daily seamless 10 km ambient gaseous pollutants (NO2, SO2, and CO) across China using machine learning with extensive input variables measured on monitors, satellites, and models. Our dataset yields a high data quality via cross-validation at varying spatiotemporal scales and outperforms most previous related studies, making it most helpful to future (especially short-term) air pollution and environmental health-related studies.
Vitali E. Fioletov, Chris A. McLinden, Debora Griffin, Ihab Abboud, Nickolay Krotkov, Peter J. T. Leonard, Can Li, Joanna Joiner, Nicolas Theys, and Simon Carn
Earth Syst. Sci. Data, 15, 75–93, https://doi.org/10.5194/essd-15-75-2023, https://doi.org/10.5194/essd-15-75-2023, 2023
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Sulfur dioxide (SO2) measurements from three satellite instruments were used to update and extend the previously developed global catalogue of large SO2 emission sources. This version 2 of the global catalogue covers the period of 2005–2021 and includes a total of 759 continuously emitting point sources. The catalogue data show an approximate 50 % decline in global SO2 emissions between 2005 and 2021, although emissions were relatively stable during the last 3 years.
Gonzalo A. Ferrada, Meng Zhou, Jun Wang, Alexei Lyapustin, Yujie Wang, Saulo R. Freitas, and Gregory R. Carmichael
Geosci. Model Dev., 15, 8085–8109, https://doi.org/10.5194/gmd-15-8085-2022, https://doi.org/10.5194/gmd-15-8085-2022, 2022
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The smoke from fires is composed of different compounds that interact with the atmosphere and can create poor air-quality episodes. Here, we present a new fire inventory based on satellite observations from the Visible Infrared Imaging Radiometer Suite (VIIRS). We named this inventory the VIIRS-based Fire Emission Inventory (VFEI). Advantages of VFEI are its high resolution (~500 m) and that it provides information for many species. VFEI is publicly available and has provided data since 2012.
Can Li, Joanna Joiner, Fei Liu, Nickolay A. Krotkov, Vitali Fioletov, and Chris McLinden
Atmos. Meas. Tech., 15, 5497–5514, https://doi.org/10.5194/amt-15-5497-2022, https://doi.org/10.5194/amt-15-5497-2022, 2022
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Satellite observations provide information on the sources of SO2, an important pollutant that affects both air quality and climate. However, these observations suffer from relatively poor data quality due to weak signals of SO2. Here, we use a machine learning technique to analyze satellite SO2 observations in order to reduce the noise and artifacts over relatively clean areas while keeping the signals near pollution sources. This leads to significant improvement in satellite SO2 data.
Vitali Fioletov, Chris A. McLinden, Debora Griffin, Nickolay Krotkov, Fei Liu, and Henk Eskes
Atmos. Chem. Phys., 22, 4201–4236, https://doi.org/10.5194/acp-22-4201-2022, https://doi.org/10.5194/acp-22-4201-2022, 2022
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The COVID-19 lockdown had a large impact on anthropogenic emissions and particularly on nitrogen dioxide (NO2). A new method of isolation of background, urban, and industrial components in NO2 is applied to estimate the lockdown impact on each of them. From 16 March to 15 June 2020, urban NO2 declined by −18 % to −28 % in most regions of the world, while background NO2 typically declined by less than −10 %.
Fei Liu, Zhining Tao, Steffen Beirle, Joanna Joiner, Yasuko Yoshida, Steven J. Smith, K. Emma Knowland, and Thomas Wagner
Atmos. Chem. Phys., 22, 1333–1349, https://doi.org/10.5194/acp-22-1333-2022, https://doi.org/10.5194/acp-22-1333-2022, 2022
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In this work, we present a novel method to infer NOx emissions and lifetimes based on tropospheric NO2 observations together with reanalysis wind fields for cities located in polluted backgrounds. We evaluate the accuracy of the method using synthetic NO2 observations derived from a high-resolution model simulation. Our work provides an estimate for uncertainties in satellite-derived emissions inferred from chemical transport model (CTM)-independent approaches.
Catherine Hardacre, Jane P. Mulcahy, Richard J. Pope, Colin G. Jones, Steven T. Rumbold, Can Li, Colin Johnson, and Steven T. Turnock
Atmos. Chem. Phys., 21, 18465–18497, https://doi.org/10.5194/acp-21-18465-2021, https://doi.org/10.5194/acp-21-18465-2021, 2021
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We investigate UKESM1's ability to represent the sulfur (S) cycle in the recent historical period. The S cycle is a key driver of historical radiative forcing. Earth system models such as UKESM1 should represent the S cycle well so that we can have confidence in their projections of future climate. We compare UKESM1 to observations of sulfur compounds, finding that the model generally performs well. We also identify areas for UKESM1’s development, focussing on how SO2 is removed from the air.
Nick Gorkavyi, Nickolay Krotkov, Can Li, Leslie Lait, Peter Colarco, Simon Carn, Matthew DeLand, Paul Newman, Mark Schoeberl, Ghassan Taha, Omar Torres, Alexander Vasilkov, and Joanna Joiner
Atmos. Meas. Tech., 14, 7545–7563, https://doi.org/10.5194/amt-14-7545-2021, https://doi.org/10.5194/amt-14-7545-2021, 2021
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The 21 June 2019 eruption of the Raikoke volcano produced significant amounts of volcanic aerosols (sulfate and ash) and sulfur dioxide (SO2) gas that penetrated into the lower stratosphere. We showed that the amount of SO2 decreases with a characteristic period of 8–18 d and the peak of sulfate aerosol lags the initial peak of SO2 by 1.5 months. We also examined the dynamics of an unusual stratospheric coherent circular cloud of SO2 and aerosol observed from 18 July to 22 September 2019.
Nicolas Theys, Vitali Fioletov, Can Li, Isabelle De Smedt, Christophe Lerot, Chris McLinden, Nickolay Krotkov, Debora Griffin, Lieven Clarisse, Pascal Hedelt, Diego Loyola, Thomas Wagner, Vinod Kumar, Antje Innes, Roberto Ribas, François Hendrick, Jonas Vlietinck, Hugues Brenot, and Michel Van Roozendael
Atmos. Chem. Phys., 21, 16727–16744, https://doi.org/10.5194/acp-21-16727-2021, https://doi.org/10.5194/acp-21-16727-2021, 2021
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We present a new algorithm to retrieve sulfur dioxide from space UV measurements. We apply the technique to high-resolution TROPOMI measurements and demonstrate the high sensitivity of the approach to weak SO2 emissions worldwide with an unprecedented limit of detection of 8 kt yr−1. This result has broad implications for atmospheric science studies dealing with improving emission inventories and identifying and quantifying missing sources, in the context of air quality and climate.
Jing Wei, Zhanqing Li, Rachel T. Pinker, Jun Wang, Lin Sun, Wenhao Xue, Runze Li, and Maureen Cribb
Atmos. Chem. Phys., 21, 7863–7880, https://doi.org/10.5194/acp-21-7863-2021, https://doi.org/10.5194/acp-21-7863-2021, 2021
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This study developed a space-time Light Gradient Boosting Machine (STLG) model to derive the high-temporal-resolution (1 h) and high-quality PM2.5 dataset in China (i.e., ChinaHighPM2.5) at a 5 km spatial resolution from the Himawari-8 Advanced Himawari Imager aerosol products. Our model outperforms most previous related studies with a much lower computation burden in terms of speed and memory, making it most suitable for real-time air pollution monitoring in China.
Nikita M. Fedkin, Can Li, Nickolay A. Krotkov, Pascal Hedelt, Diego G. Loyola, Russell R. Dickerson, and Robert Spurr
Atmos. Meas. Tech., 14, 3673–3691, https://doi.org/10.5194/amt-14-3673-2021, https://doi.org/10.5194/amt-14-3673-2021, 2021
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This study presents a new volcanic sulfur dioxide (SO2) layer height retrieval algorithm for the Ozone Monitoring Instrument (OMI). We generated a large spectral dataset with a radiative transfer model and used it to train neural networks to predict SO2 height from OMI radiance data. The algorithm is fast and takes less than 10 min for a single orbit. Retrievals were tested on four eruption cases, and results had reasonable agreement (within 2 km) with other retrievals and previous studies.
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Short summary
Air pollutants like sulfur dioxide impact human health and the environment. Our work estimated surface sulfur dioxide concentrations from satellite data over eastern China. One method used atmospheric models, and another method used machine learning. We found that compared to measurements from an air quality monitoring network, both methods accurately captured the locations of sulfur dioxide, but the machine learning method was generally much more accurate in the estimated concentrations.
Air pollutants like sulfur dioxide impact human health and the environment. Our work estimated...
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